20 citations · 20 across the 1 of their papers we have counts for
4 papers
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Ryutaro Tanno, Daniel Worrall, Enrico Kaden +6
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, little consideration has been giv…
The role of node dynamics in shaping emergent functional connectivity patterns in the brain
Michael Forrester, Stephen Coombes, Jonathan J. Crofts +2
The contribution of structural connectivity to functional brain states remains poorly understood. We present a mathematical and computational study suited to assess the structure--…
Improved fibre dispersion estimation using b-tensor encoding
Michiel Cottaar, Filip Szczepankiewicz, Matteo Bastiani +4
Measuring fibre dispersion in white matter with diffusion magnetic resonance imaging (MRI) is limited by an inherent degeneracy between fibre dispersion and microscopic diffusion a…
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh +4
In this work, we investigate the value of uncertainty modeling in 3D super-resolution with convolutional neural networks (CNNs). Deep learning has shown success in a plethora of me…